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What is Tire Defect Detection Using ViT-CNN Model about?

This paper presents an innovative hybrid ViT-CNN model for tire defect detection, combining a lightweight attention-based inception module with Vision Transformer and Convolutional Neural Network techniques. The model demonstrates high performance with a recall rate of 95.48%, precision of 96.1%, and overall accuracy of 97.33% on a dataset of over 83,000 X-ray images of tires. This approach addresses the challenges of diverse tire structures and defect types, enhancing automated inspection processes in tire

Author

Amin Alfakih

Language

EN